In [4]:
import cv2
import numpy as np
from PIL import Image, ImageDraw, ImageFont
import matplotlib.pyplot as plt
import urllib.request
# 이미지 다운로드 함수
def download_image(url, filename):
urllib.request.urlretrieve(url, filename)
# 이미지 URL (공개 도메인 이미지)
image_url = "https://upload.wikimedia.org/wikipedia/commons/3/3c/Giant_Panda_2004-03-2.jpg"
image_filename = "panda.jpg"
# 이미지 다운로드
download_image(image_url, image_filename)
# 이미지 로드
image = cv2.imread(image_filename)
image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
# 1. 이미지 필터 적용 (예: 가우시안 블러)
blurred = cv2.GaussianBlur(image_rgb, (15, 15), 0)
# 2. 엣지 감지
edges = cv2.Canny(image_rgb, 100, 200)
# 3. 객체 감지 (여기서는 얼굴 감지를 예로 들겠습니다)
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
gray = cv2.cvtColor(image_rgb, cv2.COLOR_RGB2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
# 결과 이미지 생성
result = image_rgb.copy()
for (x, y, w, h) in faces:
cv2.rectangle(result, (x, y), (x+w, y+h), (255, 0, 0), 2)
# Pillow를 사용하여 결과 표시
pil_image = Image.fromarray(result)
draw = ImageDraw.Draw(pil_image)
font = ImageFont.load_default()
draw.text((10, 10), "Detected Objects: " + str(len(faces)), font=font, fill=(255, 255, 255))
# 결과 표시
plt.figure(figsize=(20, 10))
plt.subplot(2, 2, 1)
plt.title("Original Image")
plt.imshow(image_rgb)
plt.axis('off')
plt.subplot(2, 2, 2)
plt.title("Blurred Image")
plt.imshow(blurred)
plt.axis('off')
plt.subplot(2, 2, 3)
plt.title("Edge Detection")
plt.imshow(edges, cmap='gray')
plt.axis('off')
plt.subplot(2, 2, 4)
plt.title("Object Detection")
plt.imshow(pil_image)
plt.axis('off')
plt.tight_layout()
plt.show()
